ErbB Receptor Signaling Research Articles

Identification of ferroptosis-related genes and predicted overall survival in patients with burns.

Burns are a common trauma associated with considerable mortality and morbidity. Although a lot is known regarding burns' pathogenesis, the involvement of ferroptosis is uncertain. Here, we aimed to explore vital ferroptosis-related genes and molecules in burns, through bioinformatics analysis, to uncover new effective therapeutic targets. The FerrDb database was used to acquire ferroptosis-related genes and GSE19743 was downloaded from Gene Expression Omnibus (GEO), a dataset with analysis of control and burned individuals. Hub genes were selected with Cytoscape software, and Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were conducted. Cox proportional hazard function and Kaplan-Meier survival analyses were implemented to screen prognosis-related genes. Additionally, the miRWalk database was used to acquire the miRNAs relevant to our hub genes function and analyzed for enrichment. We identified 64 differentially expressed genes and through the intersection with ferroptosis-related genes, 10 were selected as hub genes. GO analysis revealed that the hub genes' most enriched activities were response to oxidative stress, pyridine-containing compound metabolic processes, and reactive oxygen species metabolic processes. KEGG pathways' analysis showed that these overlapped genes were enriched in several pathways, namely, in VEGF signaling. Furthermore, the molecular miRNA functions significantly enriched were signal transduction and cell communication, namely, the biological pathways of the glypican pathway and the ErbB receptor signaling network. SLC40A1 and GPT2 genes were found to be associated with overall survival, suggesting an important role in burn prognosis. This study may improve our understanding of the underlying burn mechanisms and provide a new direction for the prevention of poor outcomes, advances in burns treatment, and drug development.

Loss of oligodendrocyte ErbB receptor signaling leads to hypomyelination, reduced density of parvalbumin-expressing interneurons, and inhibitory function in the auditory cortex.

For a long time, myelin was thought to be restricted to excitatory neurons, and studies on dysmyelination focused primarily on excitatory cells. Recent evidence showed that axons of inhibitory neurons in the neocortex are also myelinated, but the role of myelin on inhibitory circuits remains unknown. Here we studied the impact of mild hypomyelination on both excitatory and inhibitory connectivity in the primary auditory cortex (A1) with well-characterized mouse models of hypomyelination due to loss of oligodendrocyte ErbB receptor signaling. Using laser-scanning photostimulation, we found that mice with mild hypomyelination have reduced functional inhibitory connections to A1 L2/3 neurons without changes in excitatory connections, resulting in altered excitatory/inhibitory balance. These effects are not associated with altered expression of GABAergic and glutamatergic synaptic components, but with reduced density of parvalbumin-positive (PV+ ) neurons, axons, and synaptic terminals, which reflect reduced PV expression by interneurons rather than PV+ neuronal loss. While immunostaining shows that hypomyelination occurs in both PV+ and PV- axons, there is a strong correlation between MBP and PV expression, suggesting that myelination influences PV expression. Together, the results indicate that mild hypomyelination impacts A1 neuronal networks, reducing inhibitory activity, and shifting networks towards excitation.

Decreased expression of ErbB2 on left ventricular epicardial cells in patients with diabetes mellitus

We investigated the cell surface expression of ErbB receptors on left ventricular (LV) epicardial endothelial cells and CD105+ cells obtained from cardiac biopsies of patients undergoing coronary artery bypass grafting surgery (CABG). Endothelial cells and CD105+ non-endothelial cells were freshly isolated from LV epicardial biopsies obtained from 15 subjects with diabetes mellitus (DM) and 8 controls. The expression of ErbB receptors was examined using flow cytometry. We found that diabetes mellitus (DM) and high levels of hemoglobin A1C are associated with reduced expression of ErbB2. To determine if the expression of ErbB2 receptors is regulated by glucose levels, we examined the effect of high Glucose in human microvascular endothelial cells (HMEC-1) and CD105+ non-endothelial cells, using a novel flow cytometric approach to simultaneously determine the total level, cell surface expression, and phosphorylation of ErbB2. Incubation of cells in the presence of 25 mM d-glucose resulted in decreased cell surface but not total levels of ErbB2. The level of ErbB2 at the cell surface is controlled by disintegrin and metalloproteinase domain-containing protein 10 (ADAM10) that is expressed on LV epicardial cells. Inhibition of ADAM10 prevented the high glucose-dependent decrease in the cell surface expression of ErbB2. We suggest that high Glucose depresses ErbB receptor signaling in endothelial cells and cardiac progenitor cells via the promotion of ADAM10-dependent cleavage of ErbB2 at the cell surface, thus contributing to vascular dysfunction and adverse remodeling seen in diabetic patients.

Disentangling ERBB Signaling in Breast Cancer Subtypes-A Model-Based Analysis.

Simple SummaryBreast cancer subtypes are characterized by the expression and activity of estrogen-, progesterone- and HER2-receptors and differ by the treatment as well as patient prognosis. Tumors of the HER2-subtype overexpress this receptor and are successfully targeted with anti-HER2 therapies. We wanted to know if the HER2-receptor and the downstream signaling network act similarly also in the other subtypes and if this network could potentially be a therapeutic target beyond the HER2-positive subtype. To this end, we quantitatively assessed the wiring of signaling events in the individual subtypes to unravel the characteristics of HER-signaling. Our data along with a model-based analysis suggest that major parts of the intracellular signal transduction network are unchanged between the different breast cancer subtypes and that the clinical differences mostly come from the different levels at which these receptors are present in tumor cells as well as from the particular mutations that are present in individual tumors.Targeted therapies have shown striking success in the treatment of cancer over the last years. However, their specific effects on an individual tumor appear to be varying and difficult to predict. Using an integrative modeling approach that combines mechanistic and regression modeling, we gained insights into the response mechanisms of breast cancer cells due to different ligand–drug combinations. The multi-pathway model, capturing ERBB receptor signaling as well as downstream MAPK and PI3K pathways was calibrated on time-resolved data of the luminal breast cancer cell lines MCF7 and T47D across an array of four ligands and five drugs. The same model was then successfully applied to triple negative and HER2-positive breast cancer cell lines, requiring adjustments mostly for the respective receptor compositions within these cell lines. The additional relevance of cell-line-specific mutations in the MAPK and PI3K pathway components was identified via L1 regularization, where the impact of these mutations on pathway activation was uncovered. Finally, we predicted and experimentally validated the proliferation response of cells to drug co-treatments. We developed a unified mathematical model that can describe the ERBB receptor and downstream signaling in response to therapeutic drugs targeting this clinically relevant signaling network in cell line that represent three major subtypes of breast cancer. Our data and model suggest that alterations in this network could render anti-HER therapies relevant beyond the HER2-positive subtype.

A text-based computational framework for patient -specific modeling for classification of cancers

SummaryPatient heterogeneity precludes cancer treatment and drug development; hence, development of methods for finding prognostic markers for individual treatment is urgently required. Here, we present Pasmopy (Patient-Specific Modeling in Python), a computational framework for stratification of patients using in silico signaling dynamics. Pasmopy converts texts and sentences on biochemical systems into an executable mathematical model. Using this framework, we built a model of the ErbB receptor signaling network, trained in cultured cell lines, and performed in silico simulation of 377 patients with breast cancer using The Cancer Genome Atlas (TCGA) transcriptome datasets. The temporal dynamics of Akt, extracellular signal-regulated kinase (ERK), and c-Myc in each patient were able to accurately predict the difference in prognosis and sensitivity to kinase inhibitors in triple-negative breast cancer (TNBC). Our model applies to any type of signaling network and facilitates the network-based use of prognostic markers and prediction of drug response.

ErbB3 is a critical regulator of cytoskeletal dynamics in brain microvascular endothelial cells: Implications for vascular remodeling and blood brain barrier modulation

Neuregulin (NRG)1 - ErbB receptor signaling has been shown to play an important role in the biological function of peripheral microvascular endothelial cells. However, little is known about how NRG1/ErbB signaling impacts brain endothelial function and blood-brain barrier (BBB) properties. NRG1/ErbB pathways are affected by brain injury; when brain trauma was induced in mice in a controlled cortical impact model, endothelial ErbB3 gene expression was reduced to a greater extent than that of other NRG1 receptors. This finding suggests that ErbB3-mediated processes may be significantly compromised after injury, and that an understanding of ErbB3 function would be important in the of study of endothelial biology in the healthy and injured brain. Towards this goal, cultured brain microvascular endothelial cells were transfected with siRNA to ErbB3, resulting in alterations in F-actin organization and microtubule assembly, cell morphology, migration and angiogenic processes. Importantly, a significant increase in barrier permeability was observed when ErbB3 was downregulated, suggesting ErbB3 involvement in BBB regulation. Overall, these results indicate that neuregulin-1/ErbB3 signaling is intricately connected with the cytoskeletal processes of the brain endothelium and contributes to morphological and angiogenic changes as well as to BBB integrity.

A Text-Based Computational Framework for Patient-Specific Modeling for Classification of Cancers

Patient heterogeneity precludes cancer treatment and drug development; hence, development of methods for finding prognostic markers for individual treatment are urgently required. Here, we present Pasmopy (Patient-Specific Modeling in Python), a computational framework for stratification of patients using in silico signaling dynamics. Pasmopy converts texts and sentences on gene regulation into an executable mathematical model. Using this framework, we built a model of the ErbB receptor signaling network, trained in cultured cell lines, and performed in silico simulation of 377 breast cancer patients using The Cancer Genome Atlas (TCGA) transcriptome datasets. The temporal dynamics of Akt, Extracellular Signal-Regulated Kinase (ERK), and c-Myc in each patient were able to accurately predict the difference in prognosis and sensitivity to kinase inhibitors in triple-negative breast cancer (TNBC). Our model applies to any type of signaling network and facilitates the network-based use of prognostic markers and prediction of drug response.

A Computational Framework for Prediction and Analysis of Cancer Signaling Dynamics from RNA Sequencing Data-Application to the ErbB Receptor Signaling Pathway.

Simple SummaryTemporal signaling dynamics are important for controlling the fate decisions of mammalian cells. In this study, we developed BioMASS, a computational platform for prediction and analysis of signaling dynamics using RNA-sequencing gene expression data. We first constructed a detailed mechanistic model of early transcriptional regulation mediated by ErbB receptor signaling pathway. After training the model parameters against phosphoprotein time-course datasets obtained from breast cancer cell lines, the model successfully predicted signaling activities of another untrained cell line. The result indicates that the parameters of molecular interactions in these different cell types are not particularly unique to the cell type, and the expression levels of the components of the signaling network are sufficient to explain the complex dynamics of the networks. Our method can be further expanded to predict signaling activity from clinical gene expression data for in silico drug screening for personalized medicine.A current challenge in systems biology is to predict dynamic properties of cell behaviors from public information such as gene expression data. The temporal dynamics of signaling molecules is critical for mammalian cell commitment. We hypothesized that gene expression levels are tightly linked with and quantitatively control the dynamics of signaling networks regardless of the cell type. Based on this idea, we developed a computational method to predict the signaling dynamics from RNA sequencing (RNA-seq) gene expression data. We first constructed an ordinary differential equation model of ErbB receptor → c-Fos induction using a newly developed modeling platform BioMASS. The model was trained with kinetic parameters against multiple breast cancer cell lines using autologous RNA-seq data obtained from the Cancer Cell Line Encyclopedia (CCLE) as the initial values of the model components. After parameter optimization, the model proceeded to prediction in another untrained breast cancer cell line. As a result, the model learned the parameters from other cells and was able to accurately predict the dynamics of the untrained cells using only the gene expression data. Our study suggests that gene expression levels of components within the ErbB network, rather than rate constants, can explain the cell-specific signaling dynamics, therefore playing an important role in regulating cell fate.

Text mining in a literature review of urothelial cancer using topic model

BackgroundUrothelial cancer (UC) includes carcinomas of the bladder, ureters, and renal pelvis. New treatments and biomarkers of UC emerged in this decade. To identify the key information in a vast amount of literature can be challenging. In this study, we use text mining to explore UC publications to identify important information that may lead to new research directions.MethodWe used topic modeling to analyze the titles and abstracts of 29,883 articles of UC from Pubmed, Web of Science, and Embase in Mar 2020. We applied latent Dirichlet allocation modeling to extract 15 topics and conducted trend analysis. Gene ontology term enrichment analysis and Kyoto encyclopedia of genes and genomes pathway analysis were performed to identify UC related pathways.ResultsThere was a growing trend regarding UC treatment especially immune checkpoint therapy but not the staging of UC. The risk factors of UC carried in different countries such as cigarette smoking in the United State and aristolochic acid in Taiwan and China. GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC.ConclusionsThe risk factors of UC may be dependent on the countries and GMCSF, IL-5, Syndecan-1, ErbB receptor, integrin, c-Met, and TRAIL signaling pathways are the most relevant biological pathway associated with UC. These findings may provide further UC research directions.

The comprehensive upstream transcription and downstream targeting regulation network of miRNAs reveal potential diagnostic roles in gastric cancer

Evidence has shown that miRNAs can be regulated by multiple mechanisms and can participate in tumorigenesis and progression through binding to 3′-UTRs of target mRNAs. The present study identified differentially expressed miRNAs, mRNAs, and TFs by analyzing miRNA-Seq and mRNA-Seq data to construct a TFs/miRNAs/mRNAs regulation network for GC. We found five miRNAs (miR-18a-5p, miR-21-5p, miR-96-5p, miR-182-5p, and miR-196b-5p) that were significantly overexpressed in GC tissues. Clinical analyses indicated that higher miR-21-5p expression was associated with T3 + T4 and stage III + IV. The expression of miR-96-5p, miR-182-5p, and miR-196b-5p were positively correlated with the patients' ages. The five miRNAs had diagnostic efficacy in distinguishing GC from normal tissues. The gene interaction network showed that the five miRNAs were transcriptionally regulated by 11 TFs and negatively regulated 53 mRNA expressions through binding to the 3′-UTRs. Biological pathway analysis suggested that these TFs and target genes were involved in the p53 pathway, epithelial-to-mesenchymal transition, ErbB receptor, mTOR, VEGF, and VEGFR signaling networks. KEGG pathway analysis indicated that these genes were enriched in some cancer-associated pathways, including in GC. The five miRNAs may act as potential diagnostic markers and the TFs/miRNAs/mRNAs network could suggest a regulation mechanism of miRNAs.

MEK inhibition activates STAT signaling to increase breast cancer immunogenicity via MHC-I expression.

Aim: Immunotherapy and immune checkpoint inhibitors (ICI) have changed cancer care for many patients; however, breast cancers have exhibited minimal response to single agent ICI therapy. There is a significant need to identify novel targets capable of increasing cancer cell immunogenicity and response to ICIs in breast cancer. Mitogen activated protein kinase (MAPK) signaling is essential for many cellular processes but the relationship between MAPK signaling and cancer cell immunogenicity is less well understood. Recent reports suggest that MEK inhibition (MEKi) affects the tumor-immune microenvironment by altering the expression of interferon responsive PD-L1 and MHC-I through unknown mechanisms.Methods: Using western blotting and flow cytometry, we sought to determine whether MEKi affects JAK-STAT signaling upstream of PD-L1 and MHC-I expression in a panel of mouse mammary cancer and triple negative breast cancer cell lines.Results: The cell lines tested exhibited increased STAT activation in response to MEKi treatment. Furthermore, MEKi-induced MHC-I and PD-L1 expression are dependent upon STAT1 in MMTV-Neu cells. Interestingly, MEKi-induced STAT activation and interferon-responsive protein expression are abrogated with ErbB-family inhibitor co-treatment in MMTV-Neu cells, suggesting ErbB receptor signaling dependence, but not in basal-like cell lines. Importantly, analysis of basal-like breast cancer patient samples exhibited an inverse relationship between STAT1 and Ras/MAPK activation signatures.Conclusion: These findings suggest that MAPK signaling and STAT activation are inversely related in both mouse and human mammary tumors. This work also supports further study of MEKi to increase STAT signaling and potentially, immunotherapy responses through increased MHC-I and PD-L1 expression.

ErbB receptor signalling in MCF7 breast cancer cells: an information theoretic approach

Searchable abstracts of presentations at key conferences in endocrinology ISSN 1470-3947 (print) | ISSN 1479-6848 (online)

ErbB receptor signaling directly controls oligodendrocyte progenitor cell transformation and spontaneous remyelination after spinal cord injury.

We recently discovered a novel role for neuregulin‐1 (Nrg1) signaling in mediating spontaneous regenerative processes and functional repair after spinal cord injury (SCI). We revealed that Nrg1 is the molecular signal responsible for spontaneous functional remyelination of dorsal column axons by peripheral nervous system (PNS)‐like Schwann cells after SCI. Here, we investigate whether Nrg1/ErbB signaling controls the unusual transformation of centrally derived progenitor cells into these functional myelinating Schwann cells after SCI using a fate‐mapping/lineage tracing approach. Specific ablation of Nrg1‐ErbB receptors in central platelet‐derived growth factor receptor alpha (PDGFRα)‐derived lineage cells (using PDGFRαCreERT2/Tomato‐red reporter mice crossed with ErbB3fl/fl/ErbB4fl/fl mice) led to a dramatic reduction in P0‐positive remyelination in the dorsal columns following spinal contusion injury. Central myelination, assessed by Olig2 and proteolipid protein expression, was unchanged. Loss of ErbB signaling in PDGFRα lineage cells also significantly impacted the degree of spontaneous locomotor recovery after SCI, particularly in tests dependent on proprioception. These data have important implications, namely (a) cells from the PDGFRα‐expressing progenitor lineage (which are presumably oligodendrocyte progenitor cells, OPCs) can differentiate into remyelinating PNS‐like Schwann cells after traumatic SCI, (b) this process is controlled by ErbB tyrosine kinase signaling, and (c) this endogenous repair mechanism has significant consequences for functional recovery after SCI. Thus, ErbB tyrosine kinase receptor signaling directly controls the transformation of OPCs from the PDGFRα‐expressing lineage into PNS‐like functional remyelinating Schwann cells after SCI.

ACTG1 and TLR3 are biomarkers for alcohol-associated hepatocellular carcinoma.

Alcohol consumption is a risk factor for the development of hepatocellular carcinoma (HCC); however, the association between alcohol and HCC remains unknown. The present study aimed to identify key genes related to alcohol-associated HCC to improve the current understanding of the pathology of this disease. Alcohol-associated and non-alcohol-associated HCC samples in the GSE50579 dataset of the Gene Omnibus Database were analyzed to investigate altered gene expression. Integrated bioinformatics methods were employed to clarify the biological functions of the differentially expressed genes (DEGs), including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interactions (PPIs). The present study reported that candidate biomarker micro (mi)RNAs via TargetScan Human 7.1. DEGs and their associated miRNAs (according to bioinformatics analysis) were validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Additionally, 284 EGs from the GSE50579 dataset were revealed. In GO term analysis, DEGs were closely associated with the ‘regulation of nucleic acid metabolism’. KEGG pathway analysis indicated that the DEGs were tightly engaged in the ‘VEGF and VEGF receptor signaling network’, ‘proteoglycan syndecan-mediated signaling events’, ‘erbB receptor signaling’ and ‘β1 integrin cell surface interactions’. According to the results of PPI and heat map analysis, the main hub genes were centrin 3 (CETN3), Toll-like receptor 3 (TLR3), receptor tyrosine-protein kinase (ERBB4), heat shock protein family member 8, actin γ1 (ACTG1) and α-smooth muscle actin. it was demonstrated that the ACTG1, TLR3, miR-6819-3p and miRΝΑ (miR)-6877-3P had undefined associations. Furthermore, RT-qPCR analysis revealed that miR-6819-3p and miR-6877-3P may enhance the expression levels of ACTG1 and inhibit the expression levels of TLR3 in alcohol-associated HCC tissues. TLR3 and ACTG1 were proposed as potential biomarkers of alcohol-associated HCC. Investigation into the regulatory functions of miR-6819-3p and miR-6877-3P may provide novel insights into the treatment of alcohol-associated HCC.

Dusp6 attenuates Ras/MAPK signaling to limit zebrafish heart regeneration.

Zebrafish regenerate cardiac tissue through proliferation of pre-existing cardiomyocytes and neovascularization. Secreted growth factors such as FGFs, IGF, PDGFs and Neuregulin play essential roles in stimulating cardiomyocyte proliferation. These factors activate the Ras/MAPK pathway, which is tightly controlled by the feedback attenuator Dual specificity phosphatase 6 (Dusp6), an ERK phosphatase. Here, we show that suppressing Dusp6 function enhances cardiac regeneration. Inactivation of Dusp6 by small molecules or by gene inactivation increased cardiomyocyte proliferation, coronary angiogenesis, and reduced fibrosis after ventricular resection. Inhibition of Erbb or PDGF receptor signaling suppressed cardiac regeneration in wild-type zebrafish, but had a milder effect on regeneration in dusp6 mutants. Moreover, in rat primary cardiomyocytes, NRG1-stimulated proliferation can be enhanced upon chemical inhibition of Dusp6 with BCI. Our results suggest that Dusp6 attenuates Ras/MAPK signaling during regeneration and that suppressing Dusp6 can enhance cardiac repair.

Transcriptionally inducible Pleckstrin homology-like domain, family A, member 1, attenuates ErbB receptor activity by inhibiting receptor oligomerization

Feedback control is a key mechanism in signal transduction, intimately involved in regulating the outcome of the cellular response. Here, we report a novel mechanism by which PHLDA1, Pleckstrin homology-like domain, family A, member 1, negatively regulates ErbB receptor signaling by inhibition of receptor oligomerization. We have found that the ErbB3 ligand, heregulin, induces PHILDA1 expression in MCF-7 cells. Transcriptionally-induced PHLDA1 protein directly binds to ErbB3, whereas knockdown of PHLDA1 increases complex formation between ErbB3 and ErbB2. To provide insight into the mechanism for our time-course and single-cell experimental observations, we performed a systematic computational search of network topologies of the mathematical models based on receptor dimer-tetramer formation in the ErbB activation processes. Our results indicate that only a model in which PHLDA1 inhibits formation of both dimers and tetramer can explain the experimental data. Predictions made from this model were further validated by single-molecule imaging experiments. Our studies suggest a unique regulatory feature of PHLDA1 to inhibit the ErbB receptor oligomerization process and thereby control the activity of receptor signaling network.

SUMOylation regulates nuclear accumulation and signaling activity of the soluble intracellular domain of the ErbB4 receptor tyrosine kinase

Erb-B2 receptor tyrosine kinase 4 (ErbB4) is a kinase that can signal via a proteolytically released intracellular domain (ICD) in addition to classical receptor tyrosine kinase-activated signaling cascades. Previously, we have demonstrated that ErbB4 ICD is posttranslationally modified by the small ubiquitin-like modifier (SUMO) and functionally interacts with the PIAS3 SUMO E3 ligase. However, direct evidence of SUMO modification in ErbB4 signaling has remained elusive. Here, we report that the conserved lysine residue 714 in the ErbB4 ICD undergoes SUMO modification, which was reversed by sentrin-specific proteases (SENPs) 1, 2, and 5. Although ErbB4 kinase activity was not necessary for the SUMOylation, the SUMOylated ErbB4 ICD was tyrosine phosphorylated to a higher extent than unmodified ErbB4 ICD. Mutation of the SUMOylation site compromised neither ErbB4-induced phosphorylation of the canonical signaling pathway effectors Erk1/2, Akt, or STAT5 nor ErbB4 stability. In contrast, SUMOylation was required for nuclear accumulation of the ErbB4 ICD. We also found that Lys-714 was located within a leucine-rich stretch, which resembles a nuclear export signal, and could be inactivated by site-directed mutagenesis. Furthermore, SUMOylation modulated the interaction of ErbB4 with chromosomal region maintenance 1 (CRM1), the major nuclear export receptor for proteins. Finally, the SUMO acceptor lysine was functionally required for ErbB4 ICD-mediated inhibition of mammary epithelial cell differentiation in a three-dimensional cell culture model. Our findings indicate that a SUMOylation-mediated mechanism regulates nuclear localization and function of the ICD of ErbB4 receptor tyrosine kinase.

The ectodomain of cadherin-11 binds to erbB2 and stimulates Akt phosphorylation to promote cranial neural crest cell migration.

During development, a multi-potent group of cells known as the cranial neural crest (CNC) migrate to form craniofacial structures. Proper migration of these cells requires proteolysis of cell adhesion molecules, such as cadherins. In Xenopus laevis, preventing extracellular cleavage of cadherin-11 impairs CNC migration. However, overexpression of the soluble cleavage product (EC1-3) is capable of rescuing this phenotype. The mechanism by which EC1-3 promotes CNC migration has not been investigated until now. Here we show that EC1-3 stimulates phosphorylation of Akt, a target of PI3K, in X.laevis CNC. Through immunoprecipitation experiments, we determined that EC1-3 interacts with all ErbB receptors, PDGFRα, and FGFR1. Of these receptors, only ErbB2 was able to produce an increase in Akt phosphorylation upon treatment with a recombinant EC1-3. This increase was abrogated by mubritinib, an inhibitor of ErbB2. We were able to recapitulate this decrease in Akt phosphorylation in vivo by knocking down ErbB2 in CNC cells. Knockdown of the receptor also significantly reduced CNC migration in vivo. We confirmed the importance of ErbB2 and ErbB receptor signaling in CNC migration using mubritinib and canertinib, respectively. Mubritinib and the PI3K inhibitor LY294002 significantly decreased cell migration while canertinib nearly prevented it altogether. These data show that ErbB2 and Akt are important for CNC migration and implicate other ErbB receptors and Akt-independent signaling pathways. Our findings provide the first example of a functional interaction between the extracellular domain of a type II classical cadherin and growth factor receptors.

Abstract 4157: Co-blockade of mTORC1, ERBB and estrogen receptor signalling pathways in endocrine resistance breast cancer: Combating tumor plasticity

Abstract Introduction The majority of breast cancers (BC) are estrogen (E) receptor positive (ER+). Endocrine therapies target E stimulation of tumour growth but resistance remains problematic, often a result of enhanced crosstalk between ER and growth factor pathways. Previously we reported the antiproliferative efficacy of combining everolimus (RAD001, mTORC1 inhibitor) with endocrine therapy in resistance models, but potential routes of escape from treatment via ERBB2/3 signalling were observed. We hypothesised that combined targeting of three cellular nodes (ER, ERBB and mTORC1) may target tumour rewiring and provide enhanced long-term clinical utility in endocrine resistant BCs. Methods Several ER+ BC lines adapted to long term E deprivation (LTED), modelling relapse to an aromatase inhibitor (AI), were treated in vitro with a combination of RAD001 and neratinib (pan ERBB inhibitor) in the presence or absence of estradiol (E2), tamoxifen or fulvestrant. Effects on proliferation, cell signalling, cell cycle and transcription were assessed. Additionally, an in vivo model of AI resistance was treated with monotherapies or combinations to evaluate efficacy in delaying tumour progression. Results All cell lines showed dose dependent decreases in proliferation in response to RAD001 (IC50 0.6-50nM without E2; 1-10nM with E2). Neratinib showed a wide range of IC50 values in the presence of E2 (300-1000nM). In the absence of E2, wild type (wt) cell lines showed IC50 values in excess of 1800nM with hormetic response curves, whilst in the LTED IC50 values ranged between 400-900nM. Combination of either agent with endocrine therapy caused a concentration dependent decrease in proliferation in both wt and LTED lines but the maximum effect was observed with a triple combination of RAD001, neratinib and endocrine therapy. Expression of pS6 was suppressed by RAD001 in all cells tested, whilst neratinib caused a cell specific reduction in expression of ERBB family proteins. Upregulation of pAKT was observed in all cell lines upon treatment with RAD001. Combination of RAD001 with neratinib suppressed the upregulation of pAKT and reduced cell cycle progression. In the absence of E2, RAD001 reduced ER mediated transcription and recruitment of ER and CREB binding protein to the TFF1 promoter, contrasting with neratinib, which caused a marked increase. In vivo study using LTED tumour xenografts showed the triple combination of RAD001, neratinib and fulvestrant was the most effective at reducing tumour volume (89%, p<0.001). Antitumor effects persisted after therapy removal with exception of RAD001 alone or in combination with neratinib where a slow increase in tumour growth was observed. Conclusion The combination of RAD001, neratinib and endocrine agents may be effective in patients who have relapsed on endocrine therapy but retain a functional ER by combating ERBB pathway upregulation. Citation Format: Ricardo Ribas, Sunil Pancholi, Stephanie K. Guest, Aradhana Rani, Joanna Nikitorowicz-Buniak, Nikiana Simigdala, Allan Thornhill, Richard E. Cutler Jr, Alshad S. Lalani, Francesca Avogadri-Connors, Mitch Dowsett, Stephen R. Johnston, Lesley-Ann Martin. Co-blockade of mTORC1, ERBB and estrogen receptor signalling pathways in endocrine resistance breast cancer: Combating tumor plasticity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4157. doi:10.1158/1538-7445.AM2017-4157

Robustness analysis of the detailed kinetic model of an ErbB signaling network by using dynamic sensitivity.

The ErbB receptor signaling pathway plays an important role in the regulation of cellular proliferation, survival and differentiation, and dysregulation of the pathway is linked to various types of human cancer. Mathematical models have been developed as a practical complementary approach to deciphering the complexity of ErbB receptor signaling and elucidating how the pathways discriminate between ligands to induce different cell fates. In this study, we developed a simulator to accurately calculate the dynamic sensitivity of extracellular-signal-regulated kinase (ERK) activity (ERK*) and Akt activity (Akt*), downstream of the ErbB receptors stimulated with epidermal growth factor (EGF) and heregulin (HRG). To demonstrate the feasibility of this simulator, we estimated how the reactions critically responsible for ERK* and Akt* change with time and in response to different doses of EGF and HRG, and predicted that only a small number of reactions determine ERK* and Akt*. ERK* increased steeply with increasing HRG dose until saturation, while showing a gently rising response to EGF. Akt* had a gradual wide-range response to HRG and a blunt response to EGF. Akt* was sensitive to perturbations of intracellular kinetics, while ERK* was more robust due to multiple, negative feedback loops. Overall, the simulator predicted reactions that were critically responsible for ERK* and Akt* in response to the dose of EGF and HRG, illustrated the response characteristics of ERK* and Akt*, and estimated mechanisms for generating robustness in the ErbB signaling network.